Interactive drawing recognition processing method and apparatus thereof

ABSTRACT

A drawing is read by a scanner to create raster data. A labeling process is executed for the data to extract a contour line for each pattern element resultant from the labeling process to produce contour line data and region data to manage, in a tree structure, information related to a circumscribed rectangle of each line segment of the contour line. When the operator picks by a pointing device a predetermined region on the screen of a display and a pair of line segments for recognition, there is retrieved region data corresponding to the specified region. After extracting contour line data associated with the retrieved region data, a center line creation process is executed according to the extracted contour line data.

This application is a divisional of Ser. No. 08/625,520 filed Mar. 26,1998, now U.S. Pat. No. 5,987,173.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to an interactive drawing recognitionprocessing method which performs a vector producing process for eachpattern element, which is included in image data, for example, in orderto generate a data base of an existing drawing.

2. Description of the Related Art

To construct a data base of existing drawings such as maps and diagramsof machines, there have been proposed various drawing recognitionprocessing methods. FIG. 1 shows an example of the processing procedureof the interactive drawing recognition processing method according tothe prior art. In the interactive drawing recognition processing method,a drawing is read by a scanner to create raster data (run length data)basically in the run length form (step 52). The run length data isdisplayed on a screen of a display. Next, to vectorize or transform eachpattern or drawing elements into vectors, there is conducted, forexample, a core or center line production process. In this case, whenthe operator specifies by a position input device or a pointing device adomain or region of the drawing to be recognized on the screen, the runlength data contained in the specified domain is processed such thatcenters of the run lengths are connected to each other to produce acenter line (step 54). Interactively conducting the core productionprocess for the other drawing elements, there is attained vector data byperforming a modification of the drawing and so forth (step 56 ).Thereafter, a character recognition is accomplished for characterstrings included in the drawing and a structure forming process iscarried out, for example, to assign attributes to the pattern and toestablish relationships between patterns, thereby producing a structureddata base.

Moreover, according to a conventional line type recognition method,existing drawings such as maps and diagrams of apparatuses are firstinputted to the recognition system to attain binary image data and thena vectorizing process is conducted for the binary image data.Thereafter, when a predetermined pattern is specified, a retrieval iseffected with vector data for a series of patterns to be continued fromthe specified pattern according to a predetermined program. A check isthen made to decide whether or not the attained series of patternsrepeatedly includes the predetermined pattern, thereby recognizing theline type thereof.

Additionally, there has been conventionally proposed various map inputsystems in which a map is read, pattern elements thereof are convertedinto vector data, and patterns of houses are recognized to be assignedwith codes. For example, in an interactive map data input system of theprior art, the map is first read by a scanner to produce binary imagedata. Subsequently, the operator picks by a pointing device each patternelement to transform the element into vector data. Furthermore, theoperator picks each of the house patterns such that the systemrecognizes the house pattern and then creates a code for the pattern.Thereafter, symbols included in the map are recognized and the structureforming process is carried out, for example, to decide attributes of thepatterns and to relate the patterns to each other, thereby attaining astructured data base.

However, in the interactive drawing recognition processing method of theprior art, when producing vectors from the respective pattern elements,the run length data is directly processed to generate center lines.Consequently, in the center line generating process or a medial lineextraction, it is required to carry out several processes such asdecisions of contours and positions of run lengths. Therefore, thisleads to a problem that a long period of time is required to completelyaccomplish the center line generation for the pattern after the operatorspecifies the pattern to be recognized.

In addition, according to the conventional line type recognition method,the line type of a series of patterns is recognized at a time accordingto the vector data of the overall drawing and hence there exists aproblem of the insufficient processing speed in the recognition.Furthermore, since the line type is recognized according to the program,any line type other than those taken into consideration in the programcannot be coped with. This causes a problem in that only a preset rangeof line types can be recognized.

Moreover, according to the interactive map input system of the priorart, in the process to recognize the house patterns, the operatorspecifies the house patterns one by one, leading to a problem that aconsiderably heavy load is imposed on the operator and the process canbe achieved only at a low speed.

SUMMARY OF THE INVENTION

It is an object of the present invention to provide an interactivedrawing recognition processing method capable of decreasing a period ofwork time from when a pattern to be recognized is specified to when thecenter line generation process is completely finished for the pattern.

Another object of the present invention is to provide a line typerecognition method for use in a drawing input apparatus in which theline recognition process can be simply carried out and the range ofrecognizable line types can be easily extended.

Further, another object of the present invention is to provide a houserecognition method in a map input system in which the process can beaccomplished at a high speed while mitigating the work load imposed onthe operator.

An interactive drawing recognition processing method according to thepresent invention comprises the steps of: reading in advance a drawingas a processing object; generating a contour line data by obtaining acontour line for each pattern element which is attained from a labelingprocess for an obtained image data, and a region data which manages in atree structure regional information related with a region indicating inwhich region each line segment is contained in the overall drawing foreach line segment which constitutes a contour line. Next, when a regioncontaining a pair of line segments constituting the contour line isspecified, the region is retrieved data associated with the specifiedregion; and extracting the contour line data corresponding to the regiondata which is obtained by the retrieving, and then generating a centralline of the specified pair of line segments according to the extractedcontour line data.

An interactive drawing recognition processing method according to thepresent invention, further comprises, after generating the central lineof the pair of line segments, the steps of: tracing another pair of linesegments, which is connected to the pair of line segments, according tothe contour line data; and generating a center line of the tracedanother pair of line segments.

In an interactive drawing recognition processing method according to thepresent invention, the contour line data is undergoes a polygonalapproximation process.

A line type recognizing method according to the present invention,comprises the steps of: memorizing in advance a line type pattern datain which a reference feature is registered for each constituent elementwhich constitutes a line type pattern of each line type; generating acontour line data by taking out a contour line for each patternaccording to a binary image data obtained by reading a drawing;identifying, when a line type of a objective line to be recognized on ascreen and a position of a constituent element of the objective line, atype of the constituent element of the objective line according to thecontour line data; and extracting a feature for the constituent elementof the objective line, and then deciding whether or not the objectiveline is the same as the specified line type by comparing the extractedfeature with the reference feature corresponding to the objective line.

A house recognizing method according to the present invention, whichcomprises a step of reading in advance a map as a processing object anda step of recognizing a house pattern after converting an obtainedbinary image data to a vector data, further comprises the steps of:extracting, when a frame is specified on a screen, in the frame as arecognition objective house pattern, a pattern which has a closed-loopcontour and a size not less than a predetermined size; and indicatingwhether or not the recognition objective house pattern is registered,after shaping the extracted recognition objective house pattern into ahouse contour and displaying the house contour on the screen.

A house recognizing method according to the present invention, furthercomprises, after shaping the recognition objective house pattern intothe house contour, a step of performing, when an edge of the recognitionobjective house pattern is shifted from an edge if an already registeredhouse pattern, a connection process of removing the shift between theedges, the edges being inherently overlapped with each other.

According to the interactive drawing recognition method of the presentinvention, there are produced in advance contour line data of contourlines attained from each of the pattern element and region includinginformation related to regions to be managed in a tree structure, theinformation indicating regions in the overall drawing in which therespective line segments constituting the contour lines are included.Thanks to the provision, when a region containing a pair of linesegments included in a contour line is specified, region datacorresponding to the specified region can be efficiently retrieved.Consequently, contour line data associated with the region data obtainedas a result of the retrieval can be extracted at a high speed to achievethe center line generation.

Moreover, according to the interactive drawing recognition processingmethod of the present invention, after the center line is created for apair of line segments, it is possible to trace another pair of linesegments linked with the pertinent pairs of line segments according toonly the contour line data. Therefore, the center line generation of thetraced pair of line segments can be automatically conducted.

In accordance with the line type recognition method of the presentinvention, for each line type, there is stored line type pattern data inwhich a reference feature is registered for each constituent element ofthe line type pattern such that, according to binary image data attainedby reading a drawing, contour lines are obtained for each pattern of thedrawing to produce contour line data. When a line type of a line to berecognized on the screen and a position of a constituent element of theline are specified, the line type of the constituent element isidentified according to the line contour data and there is extracted afeature for the constituent element. Thereafter, the extracted featureis compared with the reference feature corresponding to the line torecognize the line type for each constituent element. When compared withthe conventional case in which the line type is recognized for a seriesof patterns at a time according to the vector data of the overalldrawing, the line type recognition can be more simply accomplished.Additionally, for example, when a new line type is included in a map, areference feature of each constituent element constituting a new linetype pattern of the new line type can be easily added to the existingline type pattern data. When a map having the same contents as anotheris represented in a different scale, the reference feature of each linetype beforehand registered to the line type pattern data can be easilyaltered to arbitrarily expand the range of recognizable line types.

According to the house recognition method of the present invention, whena frame is specified on a screen image, a pattern which is in a closedloop having at least a predetermined size in the frame is extracted,shaped, and displayed on the screen. Therefore, after specifying housepatterns for recognition at a time, the operator is only required toindicate whether or not each of the specified images is to be registeredaccording to the result displayed on the screen. This consequentlyreduces the work load on the operator and increases the processingspeed. In addition, since the house patterns to be recognized can bespecified at a time in the frame, operability is improved when comparedwith the conventional interactive processing method.

Furthermore, according to the house recognition method of the presentinvention, after the house patterns of the recognition objects areshaped into house contours or shapes, a necessary correction ormodification can be achieved for the house patterns when a connectionprocess is conducted for the house patterns of the recognition objectsby executing a connection process for the obtained house contours.

The interactive drawing recognition processing apparatus according tothe present invention includes an image input device for reading adrawing as a processing object and thereby attaining raster data, apointing device for indicating coordinates of a position of arecognition objective pattern in the drawing, a central processor forexecuting a labeling process for the raster data produced from the imageinput device, and a feature extracting process of extracting a featurefor each pattern element labeled and attaining element data contour lineextracting process of extracting edges of the raster data for each ofthe pattern elements and obtaining contour line data, and region datacreating process of generating region data to manage for each linesegment of the contour line in a tree structure, the information beingrelated to a circumscribed rectangle of segment is also provided. Theapparatus further includes an element file for storing the element datacreated by the central processor, contour line file for storing thecontour line data generated by the central processor, a region file forstoring the region data produced by the central processor and a vectorfile. The central processor references, when a recognition objectivepattern is specified from the pointing device, the region file to detectthe region data associated with the specified recognition objectivepattern, references the contour line file to extract the contour linedata related to the detected region data, conducts a center linecreation for each of the line segments of the extracted contour line togenerate a center line, creates vector data according to the resultantcenter line, and stores the created vector data in the vector file.

Additionally, the interactive drawing recognition processing apparatusof the present invention further includes a line type pattern file forstoring line type pattern data for each line type in which apredetermined feature is registered for each of the constituent elementsobtained by dividing a line type pattern of the line type. After thevector data is stored in the vector file, the processor references, whena line type of the recognition objective line to be recognized and aposition of a constituent element of the recognition objective line arespecified from the pointing device, the contour line file to identify atype of the constituent element according to the contour line data, andextracts a feature of the constituent element. The processor thenreferences the line type pattern file to compare the extracted featurewith the reference feature corresponding to the recognition objectiveline, and judges to determine whether or not the recognition objectiveline is of the specified line type.

Furthermore, in the interactive drawing recognition processing apparatusaccording to the present invention, after the vector data is stored inthe vector file, the central processor extracts, when a frame isspecified in the drawing by the pointing device, as a recognitionobjective house pattern having a closed-loop contour and a size not lessthan a predetermined size in the frame specified from the pointingdevice and shapes the extracted recognition objective house pattern intoa predetermined house contour.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other objects and advantages of the present invention willbecome apparent by reference to the following description andaccompanying drawings wherein:

FIG. 1 is a diagram showing the procedure of the center line generationin the interactive drawing recognition processing method of the priorart;

FIG. 2 is a diagram schematically showing the construction of a computeraided design (CAD) system utilizing an embodiment of the interactivedrawing recognition processing apparatus according to the presentinvention;

FIGS. 3A to 3D are diagrams for explaining the structure of region datain the interactive drawing recognition processing method according tothe present invention;

FIG. 4 is a diagram showing the procedure of the center line generationin the interactive drawing recognition processing method according tothe present invention;

FIGS. 5A to 5D are diagrams for specifically explaining the center linegeneration in the interactive drawing recognition processing methodaccording to the present invention;

FIG. 6 is a diagram for explaining line types as recognition objects inan embodiment of the line type recognition method according to thepresent invention;

FIG. 7 is a diagram for explaining the structure of a line type patternfile of FIG. 2;

FIG. 8 is a diagram for explaining specifications of features of therespective constituent elements of the line patterns in the line typepattern file;

FIGS. 9A to 9D are diagrams for specifically explaining constituentelements of line type patterns;

FIG. 10 is flowchart for explaining the processing procedure in anembodiment of the line type recognition method according to the presentinvention;

FIG. 11 is a diagram showing a menu screen image displayed to achievethe line type recognition;

FIGS. 12A to 12C are diagrams for concretely explaining the contents ofthe line type recognition;

FIGS. 13A and 13B are diagrams for specifically explaining the contentsof the line type recognition;

FIG. 14 is a diagram for explaining the processing procedure to registersymbol features;

FIGS. 15A and 15B are diagrams for explaining a relative positionalrelationship when the symbol includes a plurality of constituentelements;

FIG. 16 is a flowchart for explaining the processing procedure torecognize a symbol;

FIG. 17 is a flowchart for explaining the processing procedure tointeractively edit the result obtained by recognizing the symbol;

FIG. 18 is a flowchart for explaining the processing procedure to updatethe symbol feature;

FIG. 19 is a flowchart for explaining the processing procedure to updateweight coefficients;

FIG. 20 is a flowchart for explaining the processing procedure to updateweight coefficients;

FIGS. 21A to 21D are diagrams for specifically explaining the centerline generation in an embodiment of the house recognition methodaccording to the present invention;

FIG. 22 is a flowchart for explaining an embodiment of the houserecognition method in a map input system according to the presentinvention; and

FIGS. 23A to 23C are diagrams for explaining the element connectingprocess.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

(Interactive Drawing Recognition Processing Method and Apparatus Thereofaccording to the Present Invention)

As shown in FIG. 2, a computer aided design (CAD) system as anembodiment of the interactive drawing recognition processing apparatusof the present invention includes a scanner 12 as an image input device,a cathode-ray tube (CRT) display 14, a pointing device 16, a centralprocessor 18, an element file 22, a contour line file 24, a region file26, a vector file 28, a structured file 32, a line type pattern file 34,a symbol knowledge base 36, a matching file 38, a link file 40, and anedited result storage 42. Incidentally, the CAD system is employed, forexample, to produce a data base of existing drawings such as maps anddiagrams of machines.

The scanner 12 optically scans a drawing to produce binary image data asinputs to the system. The CRT display 14 displays thereon the inputtedresult.

In this system, the binary image data inputted from the scanner 12 israster data basically in the run length format used in facsimiles or thelike. The raster data is vector data of which the start point isindicated by the coordinates at which the pixel value starts changing,for example, from "0 (white)" to "1 (black)" on a scan line and thefinish point is represented by the coordinates at which the pixel valuestarts changing, for example, from "1" to "0" on the scan line.

The pointing device 16 conducts the following operations and includes akeyboard, a mouse, and the like.

(a) To indicate a recognition target pattern, data of coordinatesindicating positions of the recognition target pattern is inputted.

(b) When achieving the line type recognition, a line type to berecognized and/or a start position of the recognition are/is specified.

(c) To register a symbol, a frame is specified on the screen of the CRTdisplay 14 by the mouse and then the symbol is selected in the frame.

(d) When conducting the house recognition, a frame is specified on thescreen of the CRT display 14 by the mouse and then patterns contained inthe frame are selected at a time.

The element file 22 is used to store therein features extracted for eachpattern element data (to be simply referred to as "element data"herebelow) obtained by labeling the raster data. In this case, thefeatures of the element data include the barycenter, area, circumscribedrectangle, moment, etc. In the contour line file 24, there is storeddata of contour lines attained by extracting edges of raster data foreach element data. The contour line is approximated by a polygon andincludes many line segments. One contour line forms a closed loopincluding broken or polygonal lines. Therefore, the contour line data isrepresented as data for each contour line, the data being attained bytransforming line segments constituting the line into vectors. In thisregard, the element data are linked by the contour line data and filepointers or by address pointers on the memory.

Stored in the region file 26 is region data indicating in which regionof the overall drawing each line segment constituting the contour lineis contained. The region data is managed in a tree structure including aroot, a branch node, and a leaf. In the data management according to thetree structure, each node represents a region at an intermediate pointof subdivision of a drawing and a leaf designates a region as theminimum division unit. A pointer to contour line data contained in aregion represented by a leaf is related to the leaf and is stored in amain memory 18, of the processor 18. Consequently, when a region isspecified, the system can retrieve a leaf corresponding to the specifiedregion to decide line segments of a contour line contained in the regionaccording to pointers related to the retrieved leaf. Description will begiven of the operation related to, for example, the tree structure ofregion data related to a pattern having the shape of substantially across. FIG. 3A shows a contour line including edges of the raster datafor the cross pattern. The line segments constituting the contour lineare managed for each circumscribed rectangle associated therewith(reference is to be made to FIG. 3B). The overall drawing is split intoregions each of which includes one circumscribed rectangle of each ofthe line segments, as shown in FIG. 3C. As can be seen from FIG. 3D, theprocess of subdivision is represented in the form of a region managementtree the leaves of which correspond to the minimum partition regions.

The symbol knowledge base 36 is provided to store therein symbolknowledge representing features of symbols to be registered. Stored inthe matching file 38 are any symbols (or constituent elements) matchingan isolated raster. Additionally, the link file 40 is disposed to storetherein link data for isolated raster data, the link data denoting agrid point nearest thereto when the screen is subdivided according tothe grid unit. In the edited result storage 42, there is stored suchinformation items attained when the operator edits the recognitionresult, as symbols for which the recognition has been attempted, symbolssuccessfully recognized, symbols for which the recognition has beenfailed, and symbols erroneously recognized. The information items storedin the edited result storage 42 are utilized in the update of featuresand the like.

Particularly, the embodiment employs a region multi-dimensional (R-MD)tree to manage region data. The R-MD tree is a multi-dimensional tree inwhich information related to regions is converted into coordinates toincrease the data retrieving speed. Concretely, according to the R-MDtree, a two-dimensional circumscribed rectangle is expressed by acentral position thereof (x_(c),y_(c)) and lengths x_(w) and y_(w)thereof in x and y directions, respectively. The set of four values(x_(c),y_(c),x_(w),y_(w)) characteristic to the circumscribed rectangleare assumed to indicate a point in a four-dimensional coordinate system.A predetermined coordinate conversion is further conducted for theobtained point such that the resultant point is managed in the form of amulti-dimensional tree in the new four-dimensional coordinate system.

The central processor 18 executes predetermined processes according toan interactive drawing input program 18₂ stored therein. For example, alabeling process is conducted as a pre-processing according to the inputbinary image data (raster data); a feature extraction process and acontour extraction process are carried out to create element data,contour line data, and region data. Moreover, a center line generationis interactively accomplished for a recognition target pattern toproduce vectors according to raster data. The vector file 28 is arrangedto store therein vector data resultant from the vector producingprocess. Additionally, the central processor 18 executes a structuredecision process including an attribute assigning process to assignmeanings and attributes to patterns and a relationship establishingprocess to define semantic relationships between the patterns. Thestructured data is stored in the structured file 32, which is used as aCAD data base.

In addition, the processor 18 executes a symbol recognition process anda process in which symbols resultant from the recognition areinteractively edited on the screen and features and the like of theregistered symbols are updated according to the edited results. Theupdate process is executed by depressing "Update" button displayed inthe screen of the CRT display 14.

Furthermore, the processor 18 performs a house recognition process afterthe vector generation to recognize house patterns to produce codesassociated therewith. In this process, a shaping process and aconnection process may also be effected. The shaping process isconducted for the following reason. In a stage in which the housepatterns are simply transformed into vectors, there may exist a case inwhich one edge thereof is represented with a plurality of polygonallines, which are to be shaped into one line. Moreover, a corner of thehouse patterns may possibly have been rounded or chamfered. The roundedportion is to be shaped into the original corner. The connection processis executed in the following case. Between a house pattern as therecognition target and a house pattern beforehand registered to thesystem, when a side of the former is shifted from the associated side ofthe latter, the positional shift is to be removed by the process.

Subsequently, the interactive drawing recognition processing method ofthe embodiment will be described with reference to FIG. 4 and FIGS. 5Ato 5D. FIG. 4 is a flowchart for explaining a procedure of producingcenter lines for a recognition target pattern according to the method,whereas FIGS. 5A to 5D are diagrams for specifically explaining thecenter line generation.

First, the drawing is read by the scanner 12 to attain raster data (step2 of FIG. 4). There is obtained, for example, raster data of across-shaped pattern as shown in FIG. 5A. The central processor 18executes a labeling process for the raster data, extracts therefromfeatures of the respective pattern elements thus labeled to produceelement data, and stores the data in the element file 22. Additionally,the processor 18 obtains edges from raster data of each pattern elementto store the data of a contour line in the contour line file 24 (step4). Next, according to the contour line data, the processor 18 createsregion data for each line segment of the contour line to manageinformation related to the circumscribed rectangle in the tree structure(step 6). In this connection, the processor 18 automatically executesthe operations up to this point after the drawing is read by the scanner12. The contour line and circumscribed rectangle may be visible orinvisible to the user.

Next, the center line creation is interactively carried out for thetarget pattern. The center line creation in this case means a process todetermine a line, for example, connecting the centers of two circlesrespectively inscribed on two lines. First, the operator picks by thepointing device 16 a predetermined region (the aperture region of acursor) in the screen of the CRT display 14 to specify a pair of linesegments for the recognition thereof (step 8). In this situation, as canbe seen from FIG. 5A, the operator picks a predetermined region R₁ andthen designates two substantially parallel lines S₁ and S₂ on theleft-hand side of the cross-shaped pattern. In response thereto, thereis conducted a search through the region management tree to detect aleaf corresponding to the region R₁ designated in screen (step 12 ofFIG. 5C). According to a pointer stored in association with the leaf,the process extracts from the contour line file 24 contour line datacorresponding to line segments S₁ and S₂ (step 14). Next, as shown inFIG. 5D, the process conducts an operation to generate a center line forthe extracted two segments S₁ and S₂ to attain the center line (step16). After the center line is produced for the line segments accordingto the specified region, the system achieves a trace process for the twoline segments to continuously generate center lines. In short, since thecontour line itself is one closed line, the system directly accesses thecontour line file 24 to automatically attain line segments linked to theline segments S₁ and S₂ previously undergone the center line creation,the segments S₁ and S₂ being extended in a predetermined direction,e.g., toward the right in FIG. 5A. The obtained center lines form apolygonal line (step 18). In this process, when the target pointreaches, for example, a crosspoint of the cross-shaped pattern, thecenter line cannot be generated and hence the center line creation isstopped. Thereafter, when the operator specifies by the pointing device16 a pair of line segments as another recognition object, e.g., two linesegments S3 and S4 substantially parallel to each other on the upperportion of the cross-shaped pattern, the center line creation issimilarly carried out for these segments.

In the operation, when the center line creation is stopped, the operatormay freely edit or modify the center lines generated up to the point.For example, during the center line creation for a hand-written drawing,the operator may correct a position of a line, transform a curved lineinto a straight line, or modify a line generated by mistake.Incidentally, in the modification, only the vector data attained by thecenter line creation is modified. Namely, the original raster data iskept unchanged.

After the center line creation is performed for the contour line of adesired pattern element as above, a predetermined process is executedfor the data resultant from the center line creation. For example, aplurality of polygonal lines are approximately transformed into a line.In a case where the image includes, for example, level lines related todata of a map, the lines are smoothed in the process. The vector dataattained according to the data resultant from the center line creationis stored in the vector file 28 (step 22). Thereafter, a symbolrecognition process is conducted for symbols contained in the drawing.In addition, a structure decision process is interactively carried outsuch that the attained structure data is stored in the structured file32. Incidentally, although the symbol recognition process requires theelement data and contour line data, the contour line data is linked withthe element data. Consequently, the contour line data is obtained viathe element data in the process.

According to the interactive drawing recognition processing method ofthe embodiment, there are produced contour line data by obtaining edgesfor the respective pattern elements according to the raster data thereofand region data in which information related to a circumscribedrectangle of line segments constituting the contour line is managedaccording to a tree structure such that the contour line data issupervised by the region data. Thanks to this provision, when a regionincluding a pair of line segments is specified as the recognitiontarget, the system can efficiently retrieve region data associated withthe designated region to extract contour line data corresponding to theretrieved region data at a high speed so as to achieve the center linecreation for the specified region. Therefore, the period of time lapsedfrom when a pair of line segments are specified for the recognitiontarget to when the center line generation is finished for the linesegments can be minimized. In addition, after the center line isproduced for the pair of line segments, another pair of line segmentslinked with the line segments previously processed can be traced at ahigh speed only according to the contour line data without using theregion data. This makes it possible to automatically execute the centerline creation for the traced line segments.

Although the tree structure is a region multi-dimensional (R-MD) tree inthis embodiment, there may be used a k-d tree, or the like.

According to the interactive drawing recognition processing methoddescribed above, there are created in advance the contour line data byattaining a contour line for each image element and the region dataincluding, for each line segment constituting the contour line,information indicating a region in the overall drawing in which the linesegment exists, the information being managed according to a treestructure. Due to the contour line data and the region data, when aregion including a pair of line segments constituting a contour line isspecified, region data associated with the designated region can beeffectively retrieved and hence contour line data corresponding to theretrieved region data can be obtained at a high speed to achieve thecenter line creation for the specified region. Therefore, the period oftime necessary for the operation can be minimized.

Moreover, after the center line is produced for the pair of linesegments, another pair of line segments connected to the line segmentspreviously processed can be traced at a high speed only according to thecontour line data. Therefore, it is possible to automatically executethe center line creation for the traced line segments.

(Line Type Recognition Method of the Present Invention)

Description will be next given of an embodiment of the line typerecognition method according to the present invention. The line typerecognition method of the embodiment is employed to recognize types(line types) of lines drawn in a map and can be achieved in a CAD systemshown in FIG. 2.

According to "Kokudo Kihonzu Zushiki Do Tekiyo Kitei (Fundamental LandDiagrams and Application Rules Thereof)" published from the GeographicalSurvey Institute of the Ministry of Construction of Japan, there arestipulated many line types to be adopted in maps. In the description ofthe present invention, the line types of recognition targets areparticularly limited to the railways, boundaries, level lines, etc. asshown in FIG. 6. The line types representing railways include the JapanRailways (JR), private railway, subway, cableway, and special railroad.The line types expressing boundaries include the boundary for To, Fu,and prefectures, boundary for branch offices of Hokkaido, boundary fordistrict, city, and ward of Tokyo, boundary for vegetation, boundary forarable land, boundary for sections, and boundary for towns, villages,and designated towns. In addition, the boundaries standing for levellines include the auxiliary curved line, special auxiliary curved line,ground depression, and the like. Moreover, line types as recognitionobjects include the footpath, boundary, steep slope/relative height, andprecipice (small). Each of these line types repetitiously includes apredetermined pattern, which includes a combination of constituentelements such as a line segment, a node or branch point, a crosspoint,and an isolated point. Therefore, in this embodiment, the line type isrecognized by achieving comparison of predetermined features for eachconstituent element.

In the line type pattern file 34 shown in FIG. 2 is stored line typepattern data obtained for each line type by subdividing a line typepattern thereof into a set of elements, the data including apredetermined reference feature of each of the elements. In thisembodiment, there are five kinds of constituent elements used, such asthe line segment (ordinary line segment), bold line segment, node,crosspoint, and isolated point. The bold line segment is included forthe recognition of JR. The features, respectively, of the line segmentand bold line segment are represented by the length of line segment.Additionally, an isolated point has an area in an actual map and hencethe diameter thereof is used as the feature thereof. The feature of anode is represented by the number of branches from the node, thebranches being associated with a line entering the node. For acrosspoint, the number of lines extending or outgoing therefrom (numberof outgoing lines) is used as the feature.

The layout of the line pattern file 34 will be described by referring toFIG. 7. In this diagram, the first field "linefontmember" is disposed tostore therein the number of line types defined in the file 34. In thisexample, the number of definitions of line types is set to 20 as shownin FIG. 6. Thereafter, the features of each line type pattern aredescribed in fields enclosed by [LINEFONT] and [END]. In the fieldsrepresenting the features, the name of line type is set to a field"name", the number of elements constituting the pattern is described ina field "count", and a feature of each element is specified in a field"feature". Two numeric values are set to each of the fields "feature" inwhich the first value express the type of the element and the secondvalue specifies the feature. The values designating element types are asshown in FIG. 8 in which "0" to "4" are used to represent the ordinaryline segment, bold line segment, isolated point, node or branch point,and crosspoint, respectively. Additionally, the values specifying thefeatures are set to express those related to the elements, respectively.

Description will now be specifically given of the contents of the linepattern file 34 in association with several line types. In the firstexample, line types to represent boundaries for To (of Tokyo To), Fu(e.g., Kyoto Fu), and prefectures. As can be seen from FIG. 9A, the linetype pattern includes combinations of such four elements as isolationpoint A₁, node A₂, line segment A₃, and node A₄. Isolation point A₁ hasa diameter of 0.3 mm, line segment A₃ possesses a length of 2.5 mm, andnodes A₂ and A₄ each have two branches. Therefore, a value "4" is set tothe "count" field. Two values "2,0.3" are set to the first "feature"field as features of isolated point A₁. Set to the second "feature"field are two values "3,2" indicating features of node A₂. In the third"feature" field, there are set two values "0,2.5" as features of linesegment A₃. Features of node A₄ are set as values "3,2" to the "fourth"feature field. Description will next be given of a second examplerelated to line types representing dikes. The line type pattern isformed by combining two elements including line segment B₁ andcrosspoint B₂ as shown in FIG. 9B. The line segment B1 is 0.5 mm longand crosspoint B2 has four outgoing lines. Consequently, the "count"field is set to "2". Described in the first "feature" filed are values"0,0.5" as features of line segment B₁. Feature values of crosspoint B₂are set as "4,4" in the second "feature" field. Next, as a thirdexample, line types representing Japan Railways (JR) will be described.As can be seen from FIG. 9C, the line type pattern is constituted withcombinations of two elements, i.e., ordinary line segment C₁ and boldline segment C₂ which are 2.5 mm long. In consequence, the "count" fieldis set to "2" and the first and second "feature" fields are assignedwith feature values "0,2.5" and "1,2.5" respectively of line segments C₁and C₂. Subsequently, a fourth example of specification of line typeswill be described in conjunction with the boundary for vegetation. Asshown in FIG. 9D the line type pattern includes one constituent elementof isolated point D having a diameter of 0.3 mm. Therefore, "1" is setto the "count" field and values "2,0.3" are described in the "feature"field indicating features of isolated point D.

In this regard, when the numbers respectively of branches and outgoinglines above are employed to express features related to nodes andcrosspoints, it is impossible to discriminate, e.g., the branching stateindicating whether there exists a Y-shaped branch or T-shaped branch inthe node. However, when all features of the constituent elements arecombined with each other, the line type can be uniquely identified.Namely, even if the line type cannot be exactly discriminated inassociation with each element, there arises no problem. In this case,moreover, although an angle can be considered as the feature associatedwith nodes and crosspoints, the process to recognize the line type iscomplicated when the angle is incorporated in the system, whichconsequently is unsuitable for this embodiment.

The central processor 18 executes predetermined processes according tothe interactive drawing input program 18₂ stored therein. For example,according to the binary image data (raster data) received, the processor18 carries out in the pre-processing stage the labeling process, featureextraction process, and contour line extraction process to produceelement data, contour line data, and region data. The processor 18further conducts the line type recognition process in an interactivemanner. In the line type recognition method of the embodiment, thesystem traces raster data for the constituent elements of lines to berecognized and generates therefrom vectors while recognizing the linetypes thereof, which will be described later. Stored in the vector file28 is the vector data resultant from the line type recognition process.

Next, the line type recognition method of this embodiment will bedescribed with reference to FIGS. 10 to FIG. 13. FIG. 10 is a flowchartfor explaining the processing procedure of the line type recognitionmethod, FIG. 11 is a diagram showing the menu screen image displayed inthe line type recognition process, and FIGS. 12A to 12C and FIGS. 13Aand 13B are diagrams for specifically explaining the contents of theline type recognition process.

First, the drawing is read by the scanner 12 to attain raster datathereof as descried above. The central processor 18 conducts thelabeling process for the raster data, extracts features for each patternto create element data, and then stores the data in the element file 22.Additionally, the processor 18 obtains edges of raster data for eachpattern to create contour line data to be stored in the contour linefile 24. Subsequently, according to the contour line data, the processor18 produces region data to manage information in the tree structurerelated to a circumscribed rectangle for each line segment constitutingthe contour line.

Subsequently, the processor 18 executes the line type recognitionprocess according to the flowchart of FIG. 10. First, the operatordisplays a predetermined menu in the screen of the CRT display 14 asshown in FIG. 11 and then specifies a line type to be recognized (step102). In this example, when the operator selects a predetermined linetype from the line type list and depressed "Select" button, the linetype name is designated and the line type recognition is started for theline type. The processor 18 reads from the line type pattern file 34line type pattern data corresponding to the specified line type (step104). Thereafter, the operator picks by the pointing device 16 one pointon a constituent element of the target line on the screen of the CRTdisplay 14, thereby specifying the start point of the line typerecognition (step 106). In this connection, according to the method inwhich the operator picks one point, the processor 18 retrieves linesegments and/or two or more points in the proximity of the indicatedpoint.

In response to the specification of the recognition starting point, theprocessor 18 identifies the constituent element of the target line atthe specified position and then extracts features of the element. Forthis purpose, the processor 18 first makes a search through the vicinityof the designated point (step 112). Namely, the processor 18 carries outa retrieval through the region management tree to detect a leaf in theproximity of the specified position. According to a pointer memorized inassociation with the leaf, the processor 18 extracts from the contourline file 24 a pair of contour line data items corresponding to theelement of the target line. To decide whether or not the extracted dataitems are associated with an ordinary or bold line segment, theprocessor 18 next checks to decide whether or not the center linegeneration is possible for the data items (step 114). The center linegeneration in this case means a process to attain, for example, a linedrawn between the centers respectively of two circles inscribed on twoline segments. This process is accomplished when two contour linespossess a predetermined parallelism, e.g., when the following threeconditions are completely satisfied. The angle formed therebetween isequal to or more than 30 degrees, the distance therebetween is not lessthan a predetermined value (e.g., 1 mm), and each contour line has alength equal to or more than a predetermined value. When it isdetermined that the center line generation is possible, the processor 18executes the process for these contour lines to create a center line(step 116). In this situation, moreover, using element data linked withthe contour line data, the processor 18 decides the distance between thepaired contour lines to thereby identify that the element of the targetline is an ordinary line or a bold line. Furthermore, according to thelength of the center line, the processor 18 obtains the feature of theordinary or bold line segment.

On the other hand, when it is determined in the step 114 that the centerline generation is impossible, the processor 18 checks to decide whetherthe element of the specified target line is a node or crosspoint (step118). In this case, in the predetermined region including the element ofthe line, contour line data items representing the same pattern areentirely obtained from the contour line file 24. The processor 18 thenchecks the obtained data items to determine the number of pairs ofcontour lines having the predetermined parallelism. When there exist twoor more pairs of contour lines satisfying the condition, the processor18 assumes that the element as the recognition object is a node orcrosspoint. Thereafter, when it is detected that there exists in thepaired contour lines any set of two pairs of contour lines which areextended at least a predetermined length in the mutually opposingdirection, the element is assumed to be a crosspoint; otherwise, theelement is regarded as a node (step 122). In this situation, moreover,according to the number of sets of paired contour lines having thepredetermined parallelism, there is obtained the number of nodes orbranches. For example, when the pattern of the lines is as shown in FIG.12A, there are four sets of paired contour lines having thepredetermined parallelism in the upper and lower positions and on theright and left sides relative to the central point of the image.Moreover, toward the right and left sides, these lines oppositely extendmore than a predetermined length. Consequently, the pattern isdetermined as a crosspoint with four outgoing lines. Furthermore, whenthe pattern is as shown in FIG. 12B, there exist three pairs of contourlines having the predetermined parallelism in the left, upper-right, andlower-right positions around the center point of the figure. However,there is missing a set of lines respectively extending in the mutuallyopposite directions and hence the pattern is determined as a node withtwo branches. Additionally, when processing a pattern shown in FIG. 12C,the pattern includes three pairs of contour lines having thepredetermined parallelism in the right, left, and upper positionrelative to the center of the image and the lines extend more than thepredetermined length respectively in the right and left. Therefore, thepattern is assumed to be a crosspoint with "three" outgoing lines.

In addition, when the pattern is decided to be neither a node nor anisolated point in step 118, a check is conducted to determine whether ornot the element of the target line is an isolated point (step 124). Onthis occasion, the processor 18 obtains element data linked with thecontour line data to examine whether or not the size of thecircumscribed rectangle of the pattern represented by the contour linedata is contained in a predetermined range. If this is the case, theelement is assumed to be an isolated point and then the diameter thereofis attained according to the size of the circumscribed rectangle. On theother hand, if the element is not an isolated point, the element isother than of the five constituent elements used in the process.Consequently, the element is naturally other than any line type to berecognized. Therefore, the line type recognition process is terminated(step 132).

In this way, the element of the objective line is identified in steps116, 122, or 124 to extract a feature thereof such that a check is madeto decide whether or not the feature thus extracted matches thereference feature related to the line type pattern data read from theline type pattern file 34 (step 126). In this case, the referencefeature has a preset range to decide whether or not the extractedfeature is within the range. If mismatching results between theextracted feature and the reference feature, the element of theobjective line is other than the line types to be recognized and theline type recognition process is therefore terminated (step 132). On theother hand, when it is decided that the extracted feature matches thereference feature, the element of the objective line is recognized tocorrespond to the specified line type.

Moreover, after the extracted feature is assumed to match the referencefeature in the step 126, to continuously achieve the line typerecognition process, the processor 18 traces another line to berecognized subsequent to the pertinent constituent element and thenretrieves a contour line corresponding to the traced element (step 128).For example, when the pattern is a polygonal line as shown in FIG. 13A,since the contour line is one continuous line, there are automaticallyobtained segments S₁₃ and S₁₄ from the contour lines, the segments S₁₃and S₁₄ being connected to the line segments S₁₁ and S₁₂ just undergonethe center line generation in a predetermined direction, e.g., in theright direction. On the other hand, the pattern may be intermitteddepending on line types. For example, when processing a diagram of FIG.13B including a broken line, the processor 18 automatically obtains aparticular region R in front of a front end of constituent element Ejust recognized and then extracts contour line data from the region datain the same manner as for the process of Step 112. Incidentally, whenthe line type is initially specified, the system actually decides themethod of tracing constituent elements of the objective line accordingto the specified line type.

As above, when there is a contour line associated with the next elementto be recognized, control is transferred to step 114 to successivelyexecute the line type recognition process. In the operation, when theconstituent element to be currently recognized is assumed to have theline type specified for recognition, the processor 18 generates vectordata to connect the currently recognized element to the previouslyrecognized element and then displays the data on the screen of the CRTdisplay 14, e.g., by replacing the target line with a bold line. Inshort, when the pertinent element is an ordinary line or a bold line,the center line generation is beforehand conducted to create a centerline for the constituent element thereof and hence there is conducted aprocess to link the obtained center line with the constituent elementpreviously recognized. Additionally, when the just recognized element isa node, a crosspoint, or an isolated point, there is achieved a processto draw one line so as to establish a connection from the pertinentelement to the previously recognized element.

In this regard, when the line type recognition is accomplished up to aconstituent element arranged at an end position of the screen, theprocessor 18 automatically scrolls the screen image to continue therecognition process. Moreover, the recognition is executed in apredetermined direction beginning at a position of the image firstdesignated. However, in a case in which the elements of the objectiveline are not successively disposed in the form of a loop, when theprocess reaches an end of the screen, the operator need only depress the"Reverse" button in the screen. In response thereto, the recognitionprocess is achieved in the opposite direction beginning at the positionfirst denoted.

Thereafter, when the recognition process is completely finished insequence for all elements of lines to be recognized, there is missing acontour line corresponding to an element of the subsequent line in step122 and hence the process is terminated (step 132). The vector dataobtained through the line type recognition is stored in the vector file28. This process is followed by the structure decision process for thevector data, for example, the data is assigned with attributes and isclassified according to layers.

According to the line type recognition method of this embodiment, foreach constituent element of the line type pattern of each line type,there is beforehand memorized a line type pattern data to which areference feature is registered. According to binary image data obtainedby reading a drawing, the system produces contour line data byextracting a contour line for each pattern. When a line type of a lineto be recognized in the screen image as well as a position of aconstituent element of the objective line are specified, the systemidentifies the type of the element of the line according to the contourline data and then extracts the feature for the element of the line tothereafter compare the extracted feature with the reference featureassociated with the objective line, thereby recognizing the line typefor each element. With this provision, the line type recognition processcan be easily accomplished when compared with the conventional case inwhich the line recognition is carried out at a time for a series ofpatterns according to the vector data of the overall drawing.

In addition, when a map includes, for example, lines of a new line type,a reference feature related to each constituent element of the new linetype pattern thereof can be easily added to the existing line typepatterns. When the scale varies between two maps having the samecontents, the reference feature of each line type registered in advanceto the line type pattern data can be simply altered. In consequence, therange of recognizable line types can be freely expanded.

As described above, in accordance with the line type recognition methodof the present invention, there is beforehand stored, for eachconstituent element of the line type pattern of each line type, linetype pattern data to which a reference feature is registered. The systemproduces, according to binary image data obtained by reading a drawing,contour line data by extracting a contour line for each pattern. Whenthere are specified a line type of a line to be recognized in the screenimage as well as a position of a constituent element of the objectiveline, the system identifies the type of the element of the lineaccording to the contour line data to extract the feature for theelement of the line so as to thereafter compare the extracted featurewith the reference feature associated with the objective line, therebyrecognizing the line type for each element. When compared with theconventional case in which the line recognition is carried out at a timefor a sequence of patterns according to the overall vector data of thedrawing, the above provision facilitates the line type recognitionprocess and makes it possible to easily add a new item and to simplymodify any item in reference features of line type pattern data.Consequently, it is possible to arbitrarily expand the range ofrecognizable line types.

(Symbol Recognition Method of the Present Invention)

Referring next to FIGS. 14 to 20, description will be given of anembodiment of the symbol recognition method according to the presentinvention. The method is employed to recognize symbols drawn in a mapand can be executed in a CAD system shown in FIG. 2.

First, when the vector generation is finished for the binary image dataattained by supplying a map to the system, the operator registers symbolfeatures for predetermined symbols contained in the drawing. Whenspecifying a symbol for registration, the operator first encloses thesymbol in a frame in the screen image of the CRT display 14 and theninputs a name thereof to the system (step 202). The system then extractsa feature of the specified symbol (step 204) and stores the feature assymbol knowledge in the symbol knowledge base 36 to be incorporated inthe data base (step 206). In this fashion, to register symbols to thesystem in this embodiment, the operator need only enclose a symbol in aframe in relation to raster data and hence the registration process canbe easily conducted. In this regards, the symbol features include thearea, moment, circumscribed rectangle, coefficients of Fourier expansionof a contour line, etc. Although the area, moment, and circumscribedrectangle are obtained from the element file 22, the coefficients ofFourier expansion of the contour line are on the other hand extractedfrom the contour line data linked with the element data in this process.The coefficients obtained by executing the Fourier expansion of thecontour line express a feature of the shape of the pertinent symbol andare invariant or are kept unchanged through transformation thereof,e.g., when the symbol is enlarged or minimized. Since the symbols ofmaps are generally standardized in size, the coefficients of the Fourierexpansion of the contour line are features most significant in thesymbol recognition. However, for example, when symbols of the same typehave different meanings, the size of each symbol is required to be takeninto consideration for an appropriate recognition thereof. Therefore,the features include the area and circumscribed rectangle etc.

Furthermore, when the symbol includes a plurality of constituentelements, the system extracts the feature for each constituent elementand a relative positional relationship of each constituent elementrelative to the other elements at the same time. The positionalrelationship specifies the directions of the other constituent elementswith respect to a constituent element. In this embodiment, for example,the relative positional relationship includes eight partitions as shownin FIG. 15B. Each constituent element is assigned with values "1", "2","3", . . . , and "8" in association with presence of the other elementsrespectively in the right, upper-right, just above, upper-left, . . . ,and lower-right positions of the pertinent element. Additionally, whenthe other constituent element includes the constituent element or isincluded therein, the condition is separately specified. As can be seenfrom FIG. 15A, in a case of a symbol including a Chinese letter ""enclosed in a circle, the symbol includes three elements "", "", and thecircle. Value "1" is designated for element "" as the relativepositional relationship, and a condition that the constituent element isincluded in another constituent element is also specified. Forconstituent element "", value "5" and a condition that the constituentelement is included in another constituent element are specified. Forconstituent element "circle", a condition that the constituent elementincludes other constituent elements is designated.

Subsequently, the symbol recognition process is carried out. FIG. 16shows in a flowchart the processing procedure of recognizing a symbol.First, the system sequentially obtains an isolated raster from thescreen image (step 212). Next, the system attains from the element file22 and contour line file 24 the feature of the isolated raster. If thereexists a symbol (or a constituent element thereof) matching the rasterwith respect to the feature, the system saves the symbol (or theconstituent element) in the matching file 38 (step 214). The process isrepeatedly executed for all isolated rasters.

In this embodiment, whether or not the feature is matching the symbol isdetermined according to sum of features S, which is defined as follows.##EQU1## where, Mi (i=1, 2, . . . , n) is called normal feature and isdefined according to the distance between each feature of the registeredsymbol (to be also referred to as "reference feature value" herebelow)yi and each feature of the recognition objective symbol (to be alsoreferred to as "extracted feature value" herebelow) xi. In thisconnection, it is assumed that there exist n types of features. Normalfeature Mi is "100" when the symbol registered for the feature isidentical to that of the recognition object. The value is decreased asthe discrepancy therebetween is increased. Additionally, Wi (i=1, 2, . .. , n) indicates weight coefficients for the respective normal featuresand are normalized such that the total thereof for the respectivefeatures is 10.0. Sum of features S is obtained as above in which theresults attained by multiplying normal features Mi respectively byweight coefficients Wi are totaled for all features. When the sum offeatures S is equal to or more than a predetermined threshold value T,the symbol of the recognition object is assumed to match the registeredsymbol. When the sum of features S is less than the threshold value T,these symbols are considered to be different from each other. The reasonwhy the weight coefficients are multiplied in this way is that theprecision of recognition is increased and the recognition is facilitatedby changing the weight of recognition for each feature. Basically, thecoefficients of the Fourier expansion of the contour line are set tovalues larger than those of the other features. In addition, one symbolof the recognition object is actually compared with a plurality ofsymbols registered for recognition. Consequently, there possibly occursa case in which the symbol of the recognition object is assumed to matcha plurality of symbols registered. On this occasion, the registeredsymbol having the largest value of sum of features S is assumed to bethe final symbol resultant from the recognition.

Subsequently, the system creates link data in the grid format accordingto isolated raster data (step 216). Namely, as can be seen from FIG.15A, the screen area is split into grids such that symbols (orconstituent elements) near grid points are controlled as link data. Inthis connection, a grid point is denoted as (r,s), where r and s standfor a row number and a column number, respectively. For example, whenthe symbol includes a Chinese letter "" enclosed in a circle as shown inFIG. 15A, there is produced link data indicating that "" and a circleare elements near grid point (4,3) and "" is a constituent element neargrid point (4,4). Thereafter, the system obtains one matching symbol (orconstituent element) from the matching file 38 (step 218). When thesymbol (or constituent element) includes one isolated data item, thesymbol is outputted as the final result of recognition (step 222). Onthe other hand, when the symbol includes two or more isolated dataitems, the system conducts a proximity retrieval for each of the itemsaccording to link data. When the item is a portion of the pertinentsymbol and the matching of the relative positional relationship isobtained for the item, the system outputs the item as the final symbol(step 224). After this point, the process is repetitiously executed forall symbols (constituent elements) stored in the matching file 38.

Next, the system interactively edits the recognition results. FIG. 17 isa diagram for explaining the processing procedure to interactively editthe symbols resultant from the recognition. The symbols as therecognition results are obtained in the symbol-by-symbol manner to bedisplayed in the screen image of the CRT display 14, the symbol beingsuperimposed on the raster (step 232). The operator judges to decidewhether or not the symbol is correct (step 234). Judging that the symbolis correct and assuming that the recognition has been successfullyfinished, the operator depressed "Register" button displayed on thescreen and then the symbol is arranged on the raster (step 236). On theother hand, judging that the symbol is incorrect, the operator decideswhether or not there exists any other correct symbol registered inrelation to the raster (step 238). If this is the case, assuming that anerroneous recognition has been conducted, the operator replaces thesymbol with the correct symbol (step 242) and depresses "Register"button such that the appropriate symbol is arranged on the raster (step236). Otherwise, assuming that an undesired item has been recognized,the operator pushes "Cancel" button presented on the screen to cancelthe recognition result. When there exists another symbol as therecognition result (step 244), control is passed to step 232 tosimilarly conduct the editing operation for each symbol in theinteractive manner. Moreover, for any symbol which has not beenrecognized in the symbol recognition process, i.e., for which therecognition has failed, the operator may select in the screen apredetermined symbol not registered to dispose the symbol on the raster.According to the embodiment described above, for each recognized symbol,the operator can check the correctness thereof and/or can conductreplacement thereof while comparing the symbol with data on the raster.This facilitates the editing operation done by the operator.

At this point, information related to the results of the editingoperation is stored in the edited result storage 42. The informationincludes information items of registered symbols classified as follows,i.e., symbols successfully recognized, symbols replaced by the operatorwith erroneously recognized symbols, and symbols selected by theoperator since recognition thereof has failed.

Next, description will be given of the processing procedure of updatingthe features and weight coefficients of registered symbols. Whenrecognizing a symbol in this embodiment, the normal feature ismultiplied by weight coefficients and then the sum of the results of themultiplication is calculated for the respective features to conduct thesymbol recognition according to the obtained sum of features. Therefore,the system updates in this process the weight coefficients together withthe features. This is because the recognition is facilitated by updatingweights for recognition in relation to the respective features dependingon the edited results.

Description will be first given of the process to update features ofregistered symbols. FIG. 18 shows a flowchart to explain the processingprocedure to update symbol features. According to information stored inthe edited result storage 42, the symbols of recognition results can beclassified into three types. Assume that features of symbolssuccessfully recognized are expressed as x_(ia) (i=1, 2, . . . , n; a=1,2, . . . , L), those symbols for which the recognition has failed andwhich are specified by the operator are represented as x_(ib) (i=1, 2, .. . , n; b=1, 2, . . . , M), and those symbols which have beenerroneously recognized as registered symbols and which have beenreplaced with other symbols registered are designated as x_(ic) (i=1, 2,. . . , n; c=1, 2, . . . , N). Subscript i stands for the types offeatures and there are employed n feature types. Additionally,subscripts a, b, and c are used for discrimination between the symbolsfor each feature type and there exists L, M, and N symbols for therespective types.

In this connection, the update operation of normal feature is formulatedto obtain reference features y_(i) as follows. ##EQU2## In other words,for the features x_(ia) of symbols successfully recognized and thefeatures x_(ib) of symbols for which the recognition has failed, theratios R_(ia) and R_(ib) representing ratios of distances respectivelythereof relative to reference features y_(i) are totaled for therespective symbols to attain R_(i). For the features x_(ic) of symbolserroneously recognized, the ratios B_(ic) representing the ratios ofdistance thereof relative to reference features y_(i) are totaled forthe respective symbols to attain B_(i). It is only necessary to obtainthe features y_(i) which minimize R_(i) and which maximizes B_(i).

For this purpose, the initial values of R_(i) and B_(i) are attainedaccording to the reference features y_(i) before the update process andthen there are calculated the mean value and variance of the featuresx_(ia) of symbols successfully recognized and the features x_(ib) ofsymbols for which the recognition has failed as follows (step 225).##EQU3## where, Θ indicates the mean value of the accumulated result oft preceding items and ψ designates the variance of the accumulatedresult of t preceding items. However, the variance cannot beappropriately obtained. Next, each reference feature is divided, e.g.,by 11 in a range ##EQU4## according to the mean value and variance asfollows. ##EQU5## For the obtained reference feature y_(ik) (k=0, 1, 2,. . . , 10), the system calculates 11 values respectively of R_(i) ^(k)and B_(i) ^(k) (step 254). The system then obtains k=k_(m) whichmaximize B_(i) ^(k) -R_(i) ^(k) (step 258). Thereafter, R_(i) ^(k) andB_(i) ^(k) for the obtained k=k_(m) are respectively compared with theinitial values R_(i) and B_(i). When R_(i) ^(k) is more than the initialvalue R_(i) and B_(i) ^(k) is less than the initial value B_(i), thesystem updates the original reference value y_(i) and variance asfollows (step 258). ##EQU6## On the other hand, for the obtainedk=k_(m), when R_(i) ^(k) is equal to or less than the initial valueR_(i) or when B_(i) ^(k) is equal to or more than the initial valueB_(i), the system does not update the original reference value becausethe recognition precision is not improved.

As above, after the reference features are updated, the weightcoefficients associated with this respective features are updated. FIGS.19 and 20 are flowcharts for explaining the processing procedure toupdate the weight coefficients. The update process is accomplishedaccording to the updated reference features. Assume that the sum offeatures of symbols successfully recognized is indicated as S_(Ra) (a=1,2, . . . , L), that the sum of features of symbols for which therecognition has been failed is denoted as S_(Ub) (b=1, 2, . . . , M),and that the sum of features of symbols erroneously recognized isrepresented as S_(Oc) (c=1, 2, . . . , N). These sums are related witheach other as S_(Ra) ≧T, S_(Ub) <T, and S_(Oc) ≧T. The update of theweight coefficient is formulated to obtain weight coefficients W'_(i)(i=1, 2, . . . , n) which increases S_(Ub) to be equal to or more thanthe threshold value T and which decreases S_(Oc) to be less than thethreshold value T without reducing S_(Ra) to be equal to or less thanthe threshold value T as follows. ##EQU7##

First, according to the sum of features S_(Ub) of symbols for which therecognition has failed, the reference features M_(ib) having asignificant influence on the effect of minimizing S_(Ub) to be less thanT are ordered. That is, reference features M_(ib) are sequentiallyarranged in a descending order of the respective features and thenweight coefficients respectively of the first and second items areindicated as W¹ _(Large) and W² _(Large) (step 262). In addition,according to the sum of features S_(Ub) of symbols erroneouslyrecognized, the reference features M_(ic) having a small influence onthe effect of minimizing S_(Ob) to be equal to or more than T areordered. Namely, reference features M_(ic) are arranged in an ascendingorder of the respective features and then weight coefficientsrespectively of the last and second last items are indicated as W¹_(small) and W² _(Small) (step 264). In the process of updating weightcoefficients, the weight coefficients W^(t) _(Large) (t=1 and 2) andW^(t) _(Small) (t=1 and 2) are respectively increased and decreased byan identical quantity respectively for each set of the weightcoefficients in consideration of the condition to normalize the weightcoefficients as follows (step 266). In this regard, the other weightcoefficients are kept unchanged in the operation.

First, the process is executed for the first set (W¹ _(Large),W¹_(Small)) For simplicity of explanation, assume W_(L) =W¹ _(Large) andW_(S) =W¹ _(Small) in this case. Using first the weight coefficientW_(i) before the update operation, the system totals in step 272 thesums of features S_(Ub) for the respective symbols ##EQU8## and the sumsof features S_(Ob) for the respective symbols ##EQU9## Furthermore,assuming ρ=W_(S) /19, values of W_(L) and W_(S) are respectivelyincreased and decreased by ρ×(h+1) to resultantly produce W_(L) ^(h) andW_(S) ^(h) (h=0, 1, 2, . . . , 9). That is, ##EQU10## Moreover, in theweight coefficients W_(i) (i=1, 2, . . . , n) prior to the updateoperation, W_(L) and W_(S) are respectively replaced with W_(L) ^(h) andW_(S) ^(h) to obtain weight coefficients W'_(i) (i=1, 2, . . . , n)(step 274). Utilizing the weight coefficients W'_(i), h is sequentiallyset to an integer ranging from 0 to 9 (step 276). A check is made instep 278 to decide whether or not the value of h is equal to or lessthan nine. If this is the case, control is transferred to step 282.

In step 282, the sum of features S'_(Ra) of symbols successfullyrecognized are calculated according to the weight coefficients W'_(i)for a predetermined value of h. A check is then conducted to decidewhether or not there exists any S'_(Ra) (a=1, 2, . . . , L) which isless than the threshold value T as follows. ##EQU11## If any one ofS'_(Ra) is less than the value T, the items which have been recognizedcannot be any more recognized and hence the recognition precision islowered. In consequence, control is passed to step 276. On the otherhand, when each value of S'_(Ra) is equal to or more than the thresholdvalue T, the system totals, in step 284 according to the weightcoefficients W'_(i), the sums of features S'_(Ub) for the respectivesymbols ##EQU12## and the sums of features S'_(Ob) for the respectivesymbols ##EQU13## Comparing S'U with the initial value SU, the systemdecides whether or not S'_(U) <S_(U) holds (step 286). If S'_(U) is lessthan S_(U), the recognition precision cannot be considered to beimproved for the symbols for which the recognition has failed and hencecontrol is transferred to step 276. On the other hand, if S'_(U) isequal to or more than S_(U), S'_(o) is compared with S_(o) to determinewhether or not S'_(o) >S_(o) is satisfied (step 288). If this is thecase, there exists a possibility that an erroneously recognized symbolmay possibly be erroneously recognized again. Therefore, control ispassed to step 276. On the other hand, when S'_(o) is equal to or lessthan S_(o), W_(L) and W_(S) related to the weight coefficients W_(i) arerespectively replaced with W_(L) ^(h) and W_(S) ^(h) for the value of hin the situation to resultantly replace W_(i) with W'_(i) (step 292),thereby terminating the flowchart of FIG. 20. Incidentally, if the itemsrespectively satisfying the predetermined conditions are missing insteps 282, 286, and 288 even when the process is repeatedly conductedfor all values of h, the weight coefficients are not changed.

Next, the process executed for the first group (W¹ _(Large), W¹_(Small)) is similarly accomplished for the second group (W² _(Large),W² _(Small)). When the optimal weight coefficients are obtained, theupdate process is terminated (step 268).

In the symbol recognition method of this embodiment, the symbolsrecognized are interactively edited to be classified into symbolssuccessfully recognized, symbols for which the recognition has failed,and symbols erroneously recognized. According to the edited results,there are attained new features which minimize the distancesrespectively relative to the symbols successfully recognized and symbolsfor which the recognition has failed and which maximize the distancerelative to the symbols erroneously recognized, thereby updating thefeatures of the registered symbols to obtain a higher recognitionprecision. In addition, after the features of the registered symbols areupdated, there are obtained new weight coefficients which increase thesum of features of the symbols for which the recognition has failed andwhich decreases that of the sum features of the symbols erroneouslyrecognized without reducing the sum of features of the symbolssuccessfully recognized to be less than the threshold value in thereduction thereof. With this provision, the weight coefficients can alsobe updated to attain a higher recognition precision. In consequence,after these update operations, when there is conducted a learningoperation of the previously recognized results, the symbols for whichthe preceding recognition failed or which are erroneously recognized canbe appropriately recognized and hence the recognition precision isimproved.

In this embodiment, the update operation is effected only for two groups(W¹ _(Large), W¹ _(Small) ) and (W² _(Large), W² _(Small)). However,three or more groups may be specified for the update operation of theweight coefficients.

According to the symbol recognition method of the present inventiondescribed above, after memorizing the editing results indicating whetheror not the pertinent symbols have been successfully recognized, thefeatures of the registered symbols are updated according to the editedresults thus memorized. By conducting a learning operation for therecognized results, the recognition precision can be improved in thesymbol recognition method.

Additionally, according to the edited results obtained by editing andclassifying the recognized symbols into symbols successfully recognized,symbols for which the recognition has failed, and symbols erroneouslyrecognized, there are attained new features which minimize the distancesrespectively relative to the symbols successfully recognized and symbolsfor which the recognition has failed and which maximize the distancerelative to the symbols erroneously recognized. With this provision,there is provided a symbol recognition method capable of updating thefeatures of the registered symbols to obtain a higher recognitionprecision.

Furthermore, the normal feature generated according to the distancebetween the feature of the registered symbols and those of the symbol asthe recognition object is multiplied by the weight coefficients suchthat the results of multiplication are totaled for each feature toproduce the sum of features. When the sum of features is equal to ormore than a predetermined threshold value, the symbol is regarded as theregistered symbol. Therefore, it is possible to provide a symbolrecognition method in which the symbol recognition is facilitated byaltering the recognition weight for each feature.

(House Recognition Method of the Present Invention)

Subsequently, description will be given of the house recognition methodaccording to the present invention with reference to FIGS. 21 to 23.This method is employed to recognize a house drawn in a map and can beexecuted in the CAD shown in FIG. 2.

First, referring to the flowchart of FIG. 4, the drawing is read by thescanner 12 to create raster data (step 2). For example, assume thatthere is produced raster data of four house patterns shown in FIG. 21A.The central processor 18 conducts the labeling process according to theraster data, extracts a feature for each pattern element labeled tocreate element data, and then stores the data in the element file 22. Inaddition, for each pattern element, the processor 18 obtains edges ofthe raster data to produce contour line data and stores the data in thecontour line file 24 (step 4). The processor 18 then creates region dataaccording to the contour line data to manage in a tree structureinformation related to the circumscribed rectangle of each of the linesegments constituting the contour line (step 6).

Next, the center line generation is interactively achieved for thepattern to be recognized. In this connection, the center line generationincludes a process to obtain, for example, a line establishing aconnection between the centers of circles inscribed on two linesegments. First, the operator picks by the pointing device 16 apredetermined region on the screen of the CRT display 14 to specify apair of line segments for recognition (step 8). In this case, as can beseen from FIG. 21A, it is assumed that the operator specifies two linesegments S₃₁ and S₃₂ substantially parallel to each other over the housepattern on the left-hand side. In response thereto, as shown in FIG.21B, the system makes a search through the region management tree todetect a leaf corresponding to the predetermined region R3 denoted onthe screen (FIG. 21C, step 12). Thereafter, according to the pointermemorized in the leaf, the system extracts from the contour line file 24contour line data associated with line segments S₃₁ and S₃₂ (step 14).Next, the system carries out the center line creation for the extractedline segments S₃₁ and S₃₂ to produce a center line as shown in FIG. 21D(step 16). After the operation in which the center line is createdaccording two line segments according to the specified region, thesystem executes a trace operation for the two line segments tocontinuously generate another center line. In short, since the contourline is one successive line, the system automatically acquires directlyfrom the contour line file 24 line segments of the contour line, theline segments connected to line segments S₃₁ and S₃₂ just undergone thecenter line generation in a predetermined direction, for example, towardthe left in FIG. 21A. The system creates a center line to resultantlyproduce a polygonal line (step 18). In this process, when the positionto be processed is a crosspoint, a corner, or the like of the housepattern, there is not produced such a center line and hence the centerline generation is stopped. Thereafter, when the operator specifies fromthe pointing device 16 a pair of line segments for the subsequentrecognition, for example, two line segments S₃₃ and S₃₄ substantiallyparallel to each other on the left side of the house image on theupper-left corner, the center line creation is similarly accomplishedfor these lines. In this way, the center line production is carried outfor the overall raster data. Vector data resultant from the center linegeneration is stored in the vector file 28 (step 22).

Next, the house recognition is conducted for a specific house pattern.Assume in this situation that commands are selected to execute also theconnection process in the house recognition. First, the operator sets bythe pointing device 16 a frame on the screen of the CRT display 14 todesignate a region of the range (step 332 of FIG. 22). In this case, forsimplicity of explanation, it is assumed that the operator specifies aregion including only house pattern H₄ on the upper-right corner asshown in FIG. 23A. Moreover, assume that house patterns H₁, H₂, and H₃in the neighborhood of house pattern H₄ have beforehand been registered.When the region is specified in step 332, the system extracts an imagefrom the specified region, the image having a looped contour and a sizeequal to or more than a predetermined size (step 334). Since the housepattern is generally a closed simple pattern such as a rectangle, theabove pattern having the closed loop is regarded as a house pattern tobe recognized. Additionally, since each pattern has a certain size in amap, the system extracts patterns having a size not less than a presetsize. With this provision, such small images included in the frame asthose generally used in maps can be removed from the items to beextracted, thereby efficiently acquiring house patterns for recognition.Thereafter, the system shapes the extracted house patterns, for example,to straighten side lines and/or to transform chamfered portions intocorners so as to thereby obtain a house contour (step 336).

Subsequently, the system conducts the connection process of thepertinent house pattern with respect to the house patterns alreadyregistered (step 338). First, for each side edge of house pattern H₄,the system selects one of the registered house patterns which has theshortest distance thereto in a predetermined range. For example, housepattern H₁ is chosen for edge a4 of house pattern H₄. The system thenchecks to determine whether or not there exists edge of the registeredhouse pattern H₁ which is substantially parallel to edge a₄ of housepattern H₄ and which has a distance thereto equal to or less than apredetermined distance. In this regard, the distance is set to, e.g.,several pixels, namely, about 0.3 millimeter (mm) to about 0.4 mm.Specifically, in consideration of the line type, i.e., a bold line or anordinary line, the distance is designated with a ratio thereof relativeto the line width. Actually, even when two edges are shifted about 0.3mm to about 0.4 mm from each other, the effect thereof is not clear whenviewed by humans. However, the effect of the shift therebetween is clearwhen the image is enlarged on the screen. The connection process iseffective in a case in which, for example, the area of a lot is to becalculated and/or the data is actually used as numeric values.

When there exists for edge a₄ of house pattern H₄ any edge of registeredhouse pattern H₁ which is substantially parallel thereto and which has adistance thereto equal to or less than the predetermined distance, thesystem decides the edge for connection. In this case, edge a₁ of housepattern H₁ is selected as the connecting edge. As can be seen from FIG.23B, the system then expands, contracts, and/or moves edge a4 of housepattern H₄ so that points p₄ and q₄ at both ends of edge a₄ of housepattern H₄ respectively match points p₁ and q₁ at both ends of edge a1of house pattern H₁, thereby coupling edge a₄ of house pattern H₄ to theconnecting edge. Thereafter, the above process is similarly effected ina sequential manner for the other edges b₄, c₄, and d₄ of house patternH₄ to link edge b₄ of house pattern H₄ with edge b₃ of house pattern H₃.On the other hand, edges c₄ and d₄ of house pattern H₄ are not connectedto any edge of the registered house pattern. However, as a result of theconnection of edges a₄ and b4 of house pattern H₄, edges c₄ and d₄ areautomatically expanded, contracted, and/or moved such that recognitionobjective pattern H₄ has boundaries matching those of registered housepatterns H₁ and H₃ as shown in FIG. 23C.

As above, after the connection process is carried out for one housepattern as the object of recognition, the process result is presented onthe screen of the display 14. Since the house recognition has beenconducted for a drawing having a closed-loop contour, such patternsother than the house patterns as a circle may have been processed. Toremove such an undesired result, the operator checks to determinewhether or not the processed item is not a house pattern (step 342).When the item indicates a house, the operator depresses "Register"button. In response thereto, the objective house pattern is registeredas a code in the vector file 28. On the other hand, when the processedpattern is other than a house pattern or is not required to beregistered, the operator pushes "Cancel" button displayed on the screento cancel the registration thereof. Additionally, when the regiondesignated by the frame contains any other house pattern forrecognition, the shaping process (step 336) and connection process (step338) are similarly achieved for the pattern and then the process resultis displayed on the screen of the CRT display 14. The operator thenjudges the correctness of the result.

Thereafter, the system accomplishes the symbol recognition for symbolsincluded in the map and then carries out the structure forming ordeciding process in an interactive manner to store the resultantstructured data in the structured file 32. In this connection, thesymbol recognition process requires the element data and contour linedata. Since the contour line data is linked with the element data, thesystem acquires the contour line via the element data in this process.

According to the house recognition method in the map data input systemof this embodiment, when a frame is specified on the screen, the systemextracts a recognition objective house pattern which has a closed-loopshape and a size equal to or more than a predetermined size in the frameand conducts the shaping process and connection process for theextracted house pattern and then displays the resultant pattern on thescreen. Consequently, after specifying house patterns for recognition,the operator need only indicate necessity of registration of each of thepatterns according to the result presented on the screen. This minimizesthe burden imposed on the operator and increases the processing speed.In addition, since the operator can specify the house patterns asrecognition objects in the frame, the operability is improved whencompared with the interactive processing method of the conventionaltechnology. Moreover, after the house pattern as the recognition objectis shaped into a house contour, the connection process can be achievedfor the house contour. Therefore, the system can automatically conductnecessary modifications for the house pattern.

In the embodiment above, in a case in which the command of theconnection process is not selected in the house recognition process, itmay also be possible that the system displays, when the house pattern asthe recognition object is transformed into a house contour, the processresult on the screen so that the operator decides the correctnessthereof.

According to the house recognition method described above, when a frameis specified on the screen, the system extracts as a recognitionobjective house image a graphic pattern which has a closed-loop shapeand a size equal to or more than a predetermined size in the frame andcarries out the shaping process for the attained house pattern and thendisplays the pattern on the screen. Consequently, after specifying housepatterns for recognition at a time, the operator need only indicate thenecessity of registration for each of the patterns according to theresult presented on the screen. This mitigates the burden imposed on theoperator and hence the processing speed is increased.

Furthermore, after the house pattern as the recognition object istransformed into a house contour, the system can perform the connectionprocess for the house contour, i.e., the required modifications can beautomatically accomplished for the house pattern.

While the present invention has been described with reference to theparticular illustrative embodiments, it is not to be restricted by thoseembodiments but only by the appended claims. It is to be appreciatedthat those skilled in the art can change or modify the embodimentswithout departing from the scope and spirit of the present invention.

What is claimed is:
 1. An interactive line-type recognizing method forrecognizing interactively a line type of a line which has been specifiedto a pattern displayed by displaying a binary image data on a screen,comprising:memorizing in advance a line type pattern data in which areference feature is registered for each constituent element whichconstitutes a line type pattern of the each line type; performing alabeling process based on the binary image data obtained from a drawingto generate a contour line data by taking out a contour line for eachpattern according to the binary image data which is attained from thelabeling process; identifying, when a line type of an objective line tobe recognized on the screen and a position of a constituent element ofthe objective line has been specified, a type of the constituent elementof the objective line according to the contour line data; and extractinga feature for the constituent element of the objective line, and thendeciding whether or not the objective line is the same as the specifiedline type by comparing the extracted feature with the reference featurecorresponding to the objective line, wherein at least four features,including a line segment, a node, a crosspoint, and an isolated point,are used as the constitute element.
 2. An interactive line typerecognizing method according to claim 1, further comprising, afterdeciding the objective line is the same as the specified linetype:tracing a constituent element of another objective line subsequentto the constituent element of the objective line; and performing a linetype recognition for the traced constituent element of the anotherobjective line.
 3. An interactive line type recognizing method accordingto claim 1, further comprising, after deciding the objective line is thesame as the specified line type:generating a vector data connecting theconstituent element of the objective line to a constitute element ofpreviously recognized objective line; and displaying the vector data onthe screen.
 4. A computer program readable by machine, embodying aprogram of instructions executable by the machine to perform the stepsof claim 1 for interactive drawing recognition.
 5. An interactive houserecognizing method comprising:obtaining a binary data from a map to beprocessed, performing a labeling process based on the binary image datato generate a contour line data by taking out a contour line for eachpattern according to the binary image data which is attained from thelabeling process, recognizing a house pattern after generating a vectordata from the contour line data, extracting, when a frame is specifiedon a screen, a pattern in the frame as a recognition objective housepattern, the pattern having a closed-loop contour and a size not lessthan a predetermined size; and indicating whether or not the recognitionobjective house pattern is registered, after shaping the extractedrecognition objective house pattern into a house contour and displayingthe house contour on the screen.
 6. A house recognizing method accordingto claim 5, further comprising, after shaping the recognition objectivehouse pattern into the house contour, performing, when an edge of therecognition objective house pattern is shifted from an edge of alreadyregistered house pattern, a connection process of removing the shiftbetween the edges, the edges being inherently overlapped with eachother.
 7. A computer program readable by machine, embodying a program ofinstructions executable by the machine to perform the steps of claim 5for interactive drawing recognition.
 8. An interactive symbolrecognizing method in which a symbol to be registered is specified on ascreen in advance, a feature for the symbol is extracted to register thesymbol, and then it is decided whether or not an objective symbol is thesame as the registered symbol, the method comprising:storing an editedresult of the objective symbol relating to whether or not therecognition of the objective symbol is successful; classifying therecognized symbol into a symbol successfully recognized, a symbol forwhich the recognition is failed and a symbol erroneously recognized, inthe edited result; and updating the feature of the registered symbolbased on the edited result by obtaining a new feature which minimizes adistance relative to the symbol successfully recognized, minimizes adistance relative to the symbol for which the recognition is failed, andmaximizes a distance relative to the symbol erroneously recognized. 9.An interactive symbol recognizing method according to claim 8, furthercomprising deciding that the objective symbol is the registered symbolwhen a sum of the features is equal to or more than a predeterminedthreshold value, the sum of the features being obtained by totaling foreach feature a result of multiplication in which a normal feature ismultiplied by a weight coefficient, the normal feature being generatedbased on the distance between the feature of the registered symbol andthe feature of the objective symbol.
 10. An interactive symbolrecognizing method according to claim 9, comprising, after saidupdating, updating the weight coefficient by obtaining a new weightcoefficient which increases the sum of the features for the symbol forwhich the recognition is failed and decreases the sum of the featuresfor the symbol erroneously recognized, without decreasing the sum of thefeatures for the symbol successfully recognized less than the thresholdvalue.
 11. An interactive symbol recognizing method according to claim8, wherein the feature is an area, a moment, a circumscribed rectangleand coefficients of Fourier expansion of the contour line.
 12. Acomputer program readable by machine, embodying a program ofinstructions executable by the machine to perform the steps of claim 8for interactive drawing recognition.
 13. An interactive houserecognition processing apparatus comprising:an image input device forreading a drawing and a obtaining a binary data from the drawing:acentral processor for performing a labeling process based on the binaryimage data, a generating process of generating a vector data from acontour line data, and a pattern extracting process for extracting apattern in a frame as a recognition objective house pattern; and whereinthe central processor references the labeled binary data to generate thecontour line data and shapes the extracted recognition objective housepattern into a house contour and displays the house contour on thescreen.
 14. An interactive house recognition processing apparatusaccording to claim 13 wherein, after the recognition objective housepattern is shaped into the house contour, the central processor performsa connection process for removing a shift between edges of therecognition objective house pattern and already registered housepatterns.
 15. A computer program product comprising:a computer usablemedium having computer readable program code embodied therein for aninteractive house recognizing method, the computer readable program codein the computer program product comprising:computer readable programcode for causing a computer to obtain binary image data from a map to beprocessed, computer readable program code for causing a computer toperform a labeling process based on the binary image data to labelpattern elements and to generate contour line data by taking out acontour line for each pattern element according to the binary imagedata, computer readable program code for causing a computer to registera house pattern for each pattern element; computer readable program codefor causing a computer to extract, when a frame is specified on ascreen, a pattern in the frame as a recognition objective house pattern,the pattern having a closed-loop contour and a size not less than apredetermined size; computer readable program code for causing acomputer to shape the extracted recognition objective house pattern intoa house contour and displaying the house contour on a screen; andcomputer readable program code for causing a computer to indicatewhether or not the recognition objective house pattern is registered.16. A computer program product comprising:a computer usable mediumhaving computer readable program code embodied therein for interactiveline-type recognizing method for recognizing interactively a line typeof a line which has been specified to a pattern displayed by displayinga binary image data on a screen, the computer readable program code inthe computer program product comprising:computer readable program codefor causing a computer to memorize in advance a line type pattern datain which a reference feature is registered for each constituent elementwhich constitutes a line type pattern of the each line type; computerreadable program code for causing a computer to perform a labelingprocess based on the binary image data obtained from a drawing togenerate a contour line data by taking out a contour line for eachpattern attained from the labeling process according to the binary imagedata; computer readable program code for causing a computer to identify,when a line type of an objective line to be recognized on the screen anda position of a constituent element of the objective line has beenspecified, a type of the constituent element of the objective lineaccording to the contour line data; and computer readable program codefor causing a computer to extract a feature for the constituent elementof the objective line, and then decide whether or not the objective lineis the same as the specified line type by comparing the extractedfeature with the reference feature corresponding to the objective line,wherein at least four features, including a line segment, a node, acrosspoint, and an isolated point, are used as the constitute element.17. A program storage device readable by machine, tangibly embodying aprogram of instructions executable by the machine to perform methodsteps for recognizing interactively a line type of a line which has beenspecified to a pattern displayed by displaying a binary image data on ascreen, the method steps comprising:memorizing in advance a line typepattern data in which a reference feature is registered for eachconstituent element which constitutes a line type pattern of the eachline type; performing a labeling process based on the binary image dataobtained from a drawing to generate a contour line data by taking out acontour line for each pattern according to the binary image data whichis attained from the labeling process; identifying, when a line type ofan objective line to be recognized on the screen and a position of aconstituent element of the objective line has been specified, a type ofthe constituent element of the objective line according to the contourline data; and extracting a feature for the constituent element of theobjective line, and then deciding whether or not the objective line isthe same as the specified line type by comparing the extracted featurewith the reference feature corresponding to the objective line, whereinat least four features, including a line segment, a node, a crosspoint,and an isolated point, are used as the constitute element.
 18. A programstorage device readable by machine, tangibly embodying a program ofinstructions executable by the machine to perform method steps forinteractive house recognition, the method steps comprising:obtaining abinary data from a map to be processed; performing a labeling processbased on the binary image data to generate a contour line data by takingout a contour line for each pattern according to the binary image datawhich is attained from the labeling process; recognizing a house patternafter generating a vector data from the contour line data; extracting,when a frame is specified on a screen, a pattern in the frame as arecognition objective house pattern, the pattern having a closed-loopcontour and a size not less than a predetermined size; and indicatingwhether or not the recognition objective house pattern is registered,after shaping the extracted recognition objective house pattern into ahouse contour and displaying the house contour on the screen.
 19. Aprogram storage device readable by machine, tangibly embodying a programof instructions executable by the machine to perform method steps forinteractive symbol recognition in which a symbol to be registered isspecified on a screen in advance, a feature for the symbol is extractedto register the symbol, and then it is decided whether or not anobjective symbol is the same as the registered symbol, the method stepscomprising:storing an edited result of the objective symbol relating towhether or not the recognition of the objective symbol is successful;classifying the recognized symbol into a symbol successfully recognized,a symbol for which the recognition is failed and a symbol erroneouslyrecognized, in the edited result; and updating the feature of theregistered symbol based on the edited result by obtaining a new featurewhich minimizes a distance relative to the symbol successfullyrecognized, minimizes a distance relative to the symbol for which therecognition is failed, and maximizes a distance relative to the symbolerroneously recognized.
 20. An apparatus for recognizing interactively aline type of a line which has been specified to a pattern displayed bydisplaying a binary image data on a screen, comprising:means formemorizing in advance a line type pattern data in which a referencefeature is registered for each constituent element which constitutes aline type pattern of the each line type; means for performing a labelingprocess based on the binary image data obtained from a drawing togenerate a contour line data by taking out a contour line for eachpattern according to the binary image data which is attained from thelabeling process; means for identifying, when a line type of anobjective line to be recognized on the screen and a position of aconstituent element of the objective line has been specified, a type ofthe constituent element of the objective line according to the contourline data; and means for extracting a feature for the constituentelement of the objective line, and then deciding whether or not theobjective line is the same as the specified line type by comparing theextracted feature with the reference feature corresponding to theobjective line, wherein at least four features, including a linesegment, a node, a crosspoint, and an isolated point, are used as theconstitute element.
 21. An apparatus for symbol recognition in which asymbol to be registered is specified on a screen in advance, a featurefor the symbol is extracted to register the symbol, and then it isdecided whether or not an objective symbol is the same as the registeredsymbol, comprising:means for storing an edited result of the objectivesymbol relating to whether or not the recognition of the objectivesymbol is successful; means for classifying the recognized symbol into asymbol successfully recognized, a symbol for which the recognition isfailed and a symbol erroneously recognized, in the edited result; andmeans for updating the feature of the registered symbol based on theedited result by obtaining a new feature which minimizes a distancerelative to the symbol successfully recognized, minimizes a distancerelative to the symbol for which the recognition is failed, andmaximizes a distance relative to the symbol erroneously recognized.